A Nomogram for Diagnosing Ventilator-Associated Pneumonia Using Circulating Inflammation Indicators in ICU Patients

Area of Science:

• Critical Care Medicine
• Infectious Diseases
• Diagnostic Tools

Background:

• Ventilator-associated pneumonia (VAP) is a significant complication in intensive care unit (ICU) patients on mechanical ventilation.
• Early and accurate diagnosis of VAP is crucial for timely treatment and improved patient outcomes.
• Existing diagnostic methods may have limitations in sensitivity or specificity.

Purpose of the Study:

• To construct and validate a risk nomogram model for predicting VAP in mechanically ventilated ICU patients.
• To identify key peripheral blood inflammatory indicators associated with VAP development.
• To evaluate the diagnostic accuracy of the developed nomogram model.

Main Methods:

• A retrospective case-control study involving 55 VAP patients and 113 non-VAP patients admitted to the ICU.
• Collection of clinical data and peripheral blood inflammatory markers, including neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and systemic inflammatory response index (SIRI).
• Development of a nomogram model using logistic regression and evaluation of its diagnostic performance via ROC curve analysis.

Main Results:

• Hypoproteinemia, procalcitonin (PCT), NLR, PLR, and SIRI were identified as independent risk factors for VAP.
• The nomogram model demonstrated a high diagnostic accuracy with an area under the curve (AUC) of 0.894.
• The model achieved a sensitivity of 87.3% and a specificity of 74.3%, with good calibration and clinical utility.

Conclusions:

• Hypoproteinemia, PCT, NLR, PLR, and SIRI are significant independent risk factors for VAP in ICU patients.
• The developed nomogram model, based on accessible inflammatory indicators, offers a promising tool for early VAP diagnosis.
• Further refinement is needed for routine clinical application of this diagnostic model.